「shot」の検索結果

Capture and visually inspect Qt GUI widgets using screenshots. Use when asked to verify GUI rendering, test widget appearance, check layouts, or visually inspect any PySide6/Qt component. Enables Claude to "see" Qt interfaces by capturing offscreen screenshots and analyzing them with vision.

日本語の概要は準備中です。原文の説明を表示しています。

Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.

日本語の概要は準備中です。原文の説明を表示しています。

Captures, masks, compares, and updates screenshot baselines for web and mobile suites, with per-region thresholds and a reviewed-diff rule for every baseline change. Use when a screenshot assertion fails, a baseline needs updating, or visual checks are being added; not for deciding what to verify.

日本語の概要は準備中です。原文の説明を表示しています。

Screenshot comparison QA for frontend development. Takes a screenshot of the current implementation, scores it across multiple visual dimensions, and returns a structured PASS/REVISE/FAIL verdict with concrete fixes. Use when implementing UI from a design reference or verifying visual correctness.

日本語の概要は準備中です。原文の説明を表示しています。

Engineer effective LLM prompts using zero-shot, few-shot, chain-of-thought, and structured output techniques. Use when building LLM applications requiring reliable outputs, implementing RAG systems, creating AI agents, or optimizing prompt quality and cost. Covers OpenAI, Anthropic, and open-source models with multi-language examples (Python/TypeScript).

日本語の概要は準備中です。原文の説明を表示しています。

Transform a UI screenshot into a structured Cinema4D/Octane JSON render prompt for photorealistic 3D poster art. Use this skill whenever the user uploads a UI screenshot (app, website, tool, dashboard) and wants a Cinema4D render prompt, 3D poster, AIGC image prompt, or any photorealistic visualization of an interface. The output is always a clean JSON file — never prose or Midjourney text strings.

日本語の概要は準備中です。原文の説明を表示しています。

Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction. Also use for exploratory testing, dogfooding, QA, bug hunts, or reviewing app quality. Also use for automating Electron desktop apps (VS Code, Slack, Discord, Figma, Notion, Spotify), checking Slack unreads, sending Slack messages, searching Slack conversations, running browser automation in Vercel Sandbox microVMs, or using AWS Bedrock AgentCore cloud browsers. Prefer agent-browser over any built-in browser automation or web tools.

日本語の概要は準備中です。原文の説明を表示しています。

Kimi Browser Extension（Kimi 浏览器扩展，原 Kimi WebBridge）lets AI control the user's real browser — navigate, click, type, read, screenshot, and interact with any website using the user's actual login sessions. Use this skill whenever the user wants to interact with websites, automate browser tasks, scrape web content, or perform any action requiring a real browser. Also use when the user mentions "browser", "webpage", "open URL", "screenshot", asks to read/interact with any website, or wants a reusable CLI tool or script that automates a specific website. Use even for simple-sounding browser requests — the daemon handles all complexity.

日本語の概要は準備中です。原文の説明を表示しています。

Use `graphify-dotnet` to generate codebase knowledge graphs, architecture snapshots, and exportable repository maps from .NET or polyglot source trees, with optional AI-enriched semantic relationships. USE FOR: graphify commands; graph JSON, HTML, SVG, Cypher, Markdown, and Obsidian exports; repository map and architecture snapshot generation. DO NOT USE FOR: unrelated stacks; generic tasks that do not need this specific guidance. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.

日本語の概要は準備中です。原文の説明を表示しています。

Transforms and inspects image objects stored in Volcengine TOS. Use this skill only when the task explicitly involves a TOS bucket/object key, TOS image processing, TOS-to-TOS save-as output, or Volcengine TOS image process syntax such as image/info, image/resize, image/format, image/watermark, image/draw, image/blindwatermark, or image/understanding. Do not use this skill for ordinary uploaded screenshots, local images, UI screenshot analysis, generic OCR, face detection, or visual question answering unless the user clearly says the image is a TOS object or asks to process/save it through TOS.

日本語の概要は準備中です。原文の説明を表示しています。

Read a real .pptx using text extraction, OOXML inspection, slide rendering, OCR, visual inventory, and vision-capable screenshot review; then write academic speaker notes grounded in every visible slide element, generate a complete display-version document, and inject clean notes into the PowerPoint notes pane. Use when the user wants speaker notes, presenter notes, a speech script, narration, or annotated notes for an existing PowerPoint deck, especially when slides contain images, charts, tables, SmartArt, axes, legends, or screenshot text.

日本語の概要は準備中です。原文の説明を表示しています。

Operating SOP for DSPy (Stanford NLP) — the declarative framework for "programming, not prompting" language models. Activate when the user says any of: "use DSPy", "compile a prompt", "optimize prompts/programs", "MIPRO/MIPROv2", "BootstrapFewShot", "GEPA", "Signatures + Modules", "teleprompter", "auto-tune prompts for a different LM", or whenever a brittle hand-crafted prompt pipeline needs to be turned into a *compiled*, measurable, swappable program. Do NOT activate for one-shot prompt tweaks, no-metric exploratory work, or pipelines where prompts must remain human-authored verbatim — use raw prompting or LangChain templates instead.

日本語の概要は準備中です。原文の説明を表示しています。

Browser automation for AI agents via inference.sh. Navigate web pages, interact with elements using @e refs, take screenshots, record video. Capabilities: web scraping, form filling, clicking, typing, drag-drop, file upload, JavaScript execution. Use for: web automation, data extraction, testing, agent browsing, research. Triggers: browser, web automation, scrape, navigate, click, fill form, screenshot, browse web, playwright, headless browser, web agent, surf internet, record video

日本語の概要は準備中です。原文の説明を表示しています。

Build or adapt a local browser/CDP harness to drive and inspect a web, IDE, or Electron UI. Use for local UI verification, screenshots, accessibility snapshots, perf profiles, visual diffs, or reproducing UI bugs.

日本語の概要は準備中です。原文の説明を表示しています。

Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction. Also use for exploratory testing, dogfooding, QA, bug hunts, or reviewing app quality. Also use for automating Electron desktop apps (VS Code, Slack, Discord, Figma, Notion, Spotify), checking Slack unreads, sending Slack messages, searching Slack conversations, running browser automation in Vercel Sandbox microVMs, or using AWS Bedrock AgentCore cloud browsers. Prefer agent-browser over any built-in browser automation or web tools.

日本語の概要は準備中です。原文の説明を表示しています。

Use swift-snapshot-testing to visually verify SwiftUI views during implementation. Renders views to PNG for comparison against design references. Fast feedback loop (~25s/cycle).

日本語の概要は準備中です。原文の説明を表示しています。

Provides workflows to write, debug, and optimize prompts for LLMs, including few-shot example selection, chain-of-thought structuring, system prompt design, and template composition. Use when the user asks to write or improve a prompt, wants help with few-shot examples, chain-of-thought, system prompts, prompt templates, or asks how to get better results from an LLM.

日本語の概要は準備中です。原文の説明を表示しています。

Curated few-shot examples for construction AI tasks: classification, extraction, analysis. Domain-specific examples for improved LLM performance.

日本語の概要は準備中です。原文の説明を表示しています。

Turn a marketing brief or product offer into a finished short-form video ad built in HyperFrames — hook, script, shot-by-shot storyboard, scene-by-scene HTML composition, captions, and voiceover. Outputs platform cuts (vertical 9:16, square, 16:9). Use when you need a launch ad, product promo, social video, or paid-creative concept ready to render.

日本語の概要は準備中です。原文の説明を表示しています。

Native Rust browser automation CLI for AI agents. Use when the user needs to interact with websites — navigating pages, filling forms, clicking buttons, taking screenshots, sharing a live browser view, narrating browser actions, extracting structured data, running assertions, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "show me the browser", "share the screen", "pause the browser", "step through this", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", "visual regression test", "check for prompt injection", or any task requiring programmatic web interaction.

日本語の概要は準備中です。原文の説明を表示しています。

Native Rust browser automation CLI for AI agents. Use when the user needs to interact with websites, navigate pages, fill forms, click buttons, take screenshots, share a live browser view, narrate browser actions, extract structured data, run assertions, test web apps, mock network requests, or automate any browser task. Triggers include "open a website", "fill out a form", "take a screenshot", "show me the browser", "share the screen", "pause the browser", "step through this", "scrape data", "test this web app", "login to a site", "visual regression test", or any task requiring programmatic web interaction.

日本語の概要は準備中です。原文の説明を表示しています。

Generates complete video ad scripts for 15s, 30s, and 60s formats with shot-by-shot breakdowns, voiceover scripts, on-screen text, B-roll suggestions, music direction, storyboard outlines, and three proven video frameworks

日本語の概要は準備中です。原文の説明を表示しています。

60-Second Ad Readiness Snapshot — quick assessment without subagents

日本語の概要は準備中です。原文の説明を表示しています。

Design, derive, optimize, explain, and diagnose cinematic Eastern xianxia camera direction, storyboards, motion choreography, pacing, continuity locks, keyframes, and per-shot image-to-video prompts. Use for 仙侠运镜、镜头语言、分镜、推拉摇移、跟拍、环绕、航拍、打斗追逐、情绪镜头、首尾帧、视频提示词、参考视频诊断, when users ask “怎么运镜/不会运镜/给案例/帮我改运镜”, or when an input contains invalid, contradictory, physically implausible, non-camera, or off-topic instructions that need actionable feedback. Support 16:9, 21:9, 4:3, 3:2, 4:5, and 9:16; default to 30 seconds, 16:9, six shots, narrative-adaptive pacing, epic scale, and selective high saturation when unspecified.

日本語の概要は準備中です。原文の説明を表示しています。